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Kasia Kedzierska
I am a PhD student at the University of Oxford. As a computational biologist, I use Data Science and Machine Learning to answer biological questions. Specifically, I study cancer of the uterus and chromatin organisation in disease progression. Last summer, I joined Computational Biology Department at Novo Nordisk Research Centre in Oxford as an intern, where I was working with NLP methods and knowledge graphs. Currently, I am looking into adapting my experience from the internship to build models for investigating cancer evolution.
Selected Research Experience
Intern
Novo Nordisk Research Centre Oxford
Oxford, United Kingdom
2021
- I used NLP based methods to screen biomedical articles and identify potential therapeutic targets. I built R Shiny App to allow colleagues within the company to investigate results from our pipeline.
DPhil Candidate
Wellcome Centre for Human Genetics, Big Data Institute
University of Oxford, UK
present - 2018
- In my PhD project Functional and evolutionary characterisation of chromatin organisation in endometrial cancer I am looking at how chromatin organisation influences disease progression in cancer of the uterus.
- Mentored by D. Church and D. Woodcock
- Currently I’m working on building and refining ML models of cancer evolution.
Education
DPhil. Candidate, Genomic Medicine and Statistics
Nuffield Department of Medicine, Brasenose College
University of Oxford, UK
present - 2018
- PhD fully funded by Wellcome Trust Four-year PhD Studentships in Science
M. Sc. Eng., Biotechnology
Warsaw University of Technology
Warsaw, Poland
2018 - 2015
- Master thesis: - Analysis of the mutational burden across gene sets in cancer awarded the title of The Best Master Thesis in Bioinformatics defended in 2018.
Selected Publications
Full list of publication on my Google Scholar profile scholar.google.com/citations?user=Yv6poTwAAAAJ.
Multi-omics analyses of early liver injury reveals cell-type-specific transcriptional and epigenomic shift
M. Migdal, E. Tralle, K. A. Nahia, L. Bugajski, K. Z. Kedzierska, F. Garbicz, K. Piwocka, C. L. Winata, M. Pawlak
BMC Genomics
2021
The MLH1 polymorphism rs1800734 and risk of endometrial cancer with microsatellite instability
H. Russell, K. Kedzierska, D. D. Buchanan, R. Thomas, E. Tham, M. Mints, A. Keränen, G. G. Giles, M. C. Southey, R. L. Milne, I. Tomlinson, D. Church, A. B. Spurdle, T. A. O’Mara and A. Lewis
Clinical Epigenetics
2020
Dynamics of cardiomyocyte transcriptome and chromatin landscape demarcates key events of heart development
M. Pawlak, K. Z. Kedzierska, M. Migdal, K. A. Nahia, J. A. Ramilowski, L. Bugajski, K. Hashimoto, A. Marconi, K. Piwocka, P. Carninci and C. L. Winata
Genome Research
2019
SONiCS: PCR stutter noise correction in genome-scale microsatellites
K. Z. Kedzierska, L. Gerber, D. Cagnazzi, M. Krützen, A. Ratan, L. Kistler
Bioinformatics
2018
Selected Talks and Posters
Systematic characterisation of chromatin modifiers in endometrial cancer
European Association for Cancer Research 2022 Congress
Seville, Spain
2022
Analysis of the mutational burden across gene sets in cancer
Polish Bioinformatics Society Symposium
Cracow, Poland
2019
- Invited talk
Differential mutation analysis across gene sets in cancers
Cold Spring Harbor, NY, USA
2018
- Poster
Selected Awards and Honours
Senior Hulme Scholarship
Brasenose College, University of Oxford
Oxford, UK
present - 2021
- Senior Hulme Scholarship is awarded by Brasenose College, University of Oxford to DPhil students whose academic performance is deemed to be exceptional.
Graduate Prize in the ‘Outstanding work outside degree’ category
Nuffield Department of Medicine, University of Oxford
Oxford, UK
2022 - 2021
- Each year Nuffield Department of Medicine, based on nominations, awards selected PhD students based on their performance within and outside of their degree.
Attended Workshops, Summer Schools
Machine Learning Summer School
Imperial College London, University College London
London, United Kingdom
2019
Teaching Experience
Unsupervised learning
NGSchool2022: Machine Learning in Computational Biology
Jablonna, Poland
2022
- I co-led, with Kaspar Märtens, lecture and tutorial sessions on unsupervised learning and its use cases in computational biology. All materials are availble at github.com/kzkedzierska/ngs22_unsupervised.
Data visualization in bioinformatics - hackathon mentor
Online hackathon NGSprint
Discord
2021
- I led the hackathon in data viusalisation with emphasis on computational biology. Under my supervision, 3 teams of around 5 people each, created interactive and captivating visualisation. Teaching materials are available at github.com/kzkedzierska/NGSprint_data_viz.
Online tutorials: Python for Data Science and Introduction to Python
YouTube
2020
- I led two Python tutorials: Introduction to Python kasia.codes/talk/intro_to_python/ and Python for Data Science kasia.codes/talk/py4ds/.
Introduction to R
Wellcome Centre for Human Genetics
Oxford, United Kingdom
2019
- 8 week course in Introduction to R, Data Manipulation, Data Visualisation and RNA-seq data analysis.
- Materials available on github/kzkedziersa/r_intro
Introduction to Managing Code with Git
Wellcome Centre for Human Genetics
Oxford, United Kingdom
2020 - 2019
- I led a 2-hour introduction to working with Git. Materials, including slides and exercises are available at kasia.codes/talk/into_to_git/.
Selected Grants
Visegrad Grant to organize NGSchool2022
N/A
2022 - 2020
- 32,190 EUR awarded towards organising affordable training and conference focusing on ML application in Computational Biology. During this project I managed an international team of volunteers and led the organisation of summer school, conference, online seminars and hackathon.
Non-profit Work
President
N/A
present - 2018
- The goal of the Society is to promote and support science, with emphasis on computational biology.
- President since 2019; Vice President 2018 - 2019, Founder